Abstract
Real time estimation of soil moisture and crop yield plays an important role for best irrigation management practices especially in arid and semiarid regions. A simulation model able of real time estimating and forecasting soil water storage and corn yield response to soil moisture was developed by combining two existing models. Soil water storage was estimated through the soil water balance equation considering the uncertainty of evapotranspiration and combing with Kalman filter technique. Crop dry matter and grain yield were simulated by using a functional relationship between yield and soil moisture. Some improvements have been made in the response function by considering different impacts of moisture stress on crop growth and yield for the different growing stages. Four years data sets collected in an experimental station in the North China Plain were used to calibrate and test the model. Results indicate that soil moisture storage in the soil profile estimated and predicted by the model agrees well with the measured data, and the relative error of yield prediction is around 10%, which means that the combined model and the methodology applied are capable of predicting crop yield and soil water storage dynamics.
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References
Aboitiz M, Labadie J W and Heermann D F 1986 Stochastic soil moisture estimation and forecasting for irrigated fields. Water Resour. Res. 22, 180–190.
Allen R G, Pereira L S, Raes D and Smith M 1998 Crop Evapotranspiration. Guidelines for Computing Crop Water Requirements, FAO Irrigation and Drainage Paper 56, FAO, Rome.
Chen Y, Guo G, Wang G, Kang S, Luo H and Zhang D (Eds.) 1995 Main Crop Water Requirement and Irrigation of China. China Water Power Press, Beijing, 376 pp. (in Chinese).
Childs S W, Gilley J R and Splinter W E (1977) A simplified model of corn growth under moisture stress. Transact. Am. Soc. Agricult. Engin. 20, 858–865.
Cui Y, Mao Z and Li Y 2002 Temporal and spatial variation of rice water production function. Adv. Water Sci. (in Chinese), 13, 484–4190.
Curry R B 1971 Dynamic simulation of plant growth. I. Development of a model. Transact. Am. Soc. Agricult. Engin. 14, 946–959.
Dierckx J, Gilley J R, Feyen J and Belmans C 1988 Simulation of the soil-water dynamics and corn yields under deficit irrigation. Irrigat. Sci. 9, 105–125.
Dinar A, Knapp K C and Rhoades J D 1986 Production function for cotton with dated irrigation quantities and qualities. Water Resour. Res. 22, 1519–1525.
Duncan W G and Hesketh J D 1968 Net photosynthesis rates, relative leaf growth rates, and leaf numbers of 22 maize grown at eight temperatures. Crop Sci. 8, 670–674.
Feddes R A 1987 Simulating water management and crop production with the SWACRO model. International Workshop on Land Drainage, Ohio State University, Columbus.
Guo Q, Lei Z and Yang S 1997 An investigation of soil water balance under the conditions of crop growth. J. Hydraul. Engin. Special issue, 40–46 (in Chinese).
Hanway J J 1963 Growth stages of corn (Zea mays L.). Agron. J. 55, 487–492.
Helweg O J 1991 Functions of crop yield from applied water. Agron. J. 83(4), 769–773.
Huang G, Shen R and Zhang Y 1999 Study on dynamic crop-water production function model for summer corn. Proc. International Conference on Agricultural Engineering (99-ICAE), China Agricultural University Press, Beijing, II, 309–317.
Huang G, Shen R and Zhang Y 1997 Estimation and forecasting of soil water regimes considering climatic uncertainty. J. Hydraul. Engin. Special issue, 195–203 (in Chinese).
Jensen M E 1968 Water consumption by agricultural plants. In Water Deficits and Plant Growth, Ed. T T Kozlowski, Vol. 2, Academic Press, New York.
Jensen M E and Wright J L 1987 The role of evapotranspiration models in irrigation scheduling. Trans. ASAE 21, 82–87.
Jones C A and Kiniry J R 1986 A simulation model of maize growth and development. College station US, Texas A&M University Press.
Kang S and Zhang M 1992 Crop water production function and optimal allocation irrigation water use. Proceedings of International Conference on Advances in Planning, Design and Management of Irrigation Systems as Related to Sustainable Land Use, pp. 801–807. Catholic University of Leuven, Belgium.
Kemp P R, Reynolds J F, Pachepsky Y A and Chen J L 1997 A comparative modeling study of soil water dynamics in a desert ecosystem. Water Resour. Res. 33, 73–90.
Letey J, Dinar A and Knapp K C 1985 Crop-water production function model for saline irrigation waters. Soil Sci. Soc. Am. J. 49, 1005–1009.
Morgan T H, Biere A W and Kanemasu E T 1980 A dynamic model of corn yield response to water. Water Resour. Res. 16, 59–64.
Or D and Hanks R J 1992 Spatial and temporal soil water estimation considering soil variability and evapotranspiration uncertainty. Water Resour. Res. 28, 803–814.
Place R E and Brown D M 1987 Modeling corn yields from soil moisture estimates: Description, sensitivity analysis and validation. Agricult. For. Meterorol. 41, 31–35.
Pereira L S, Liang R J, Musy A and Hann M (Eds.) 1998 Water and Soil Management for Sustainable Agriculture in the North China Plain. Departamento de Engenharia Rural, Instituto Superior de Agronomia Lisboa.
Rekolainen S, Gouy V, Francaviglia R, Eklo O M, Barlund I and Vanclooster M 2000 Simulation of soil water, bromide and pesticide behaviour in soil with the GLEAMS model. Agricult. Water Manage. 44, 201–224.
van Kenlen H 1982 Crop production under semi-arid conditions, as determined by nitrigeb and moisture availability. In Simulation Monographs. Eds. F W T Penning de Vires and H H van Laar. pp. 234–251. PUDOC, Wageningen, Netherlands.
Xie J (Ed.) 1990 Time Series Analysis. (in Chinese). Peking University Press, Beijing. 359 pp.
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Huang, G. Modeling soil water regime and corn yields considering climatic uncertainty. Plant and Soil 259, 221–229 (2004). https://doi.org/10.1023/B:PLSO.0000020966.88449.8f
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DOI: https://doi.org/10.1023/B:PLSO.0000020966.88449.8f